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In my country, we have a 3 month notice aswell and yes it does also apply in reverse. You can negociate to lower the period but most of the time the company will decline your request. For high-demand jobs it is a nightmare for everyone.


Pardon my ignorance but what tools/frameworks are used to design these kind of pages? It's very pleasing to the eyes



Not everyone is from the US...


I'm not from Europe, but if I saw "BBC converts night images to perfect daylight in ~1 second", I would assume it meant the British Broadcasting Corporation. CNN is just as big of a name. His point is absolutely relevant.

Said differently: The percentage of people who are not from the US - but are aware of CNN as the Cable News Network, is higher than the percentage of people who are not machine learning experts - but are aware of CNN as a Convolutional Neural Network


Not even close to being American and still see CNN as the News Network.

Agree that title should be changed.


We get CNN.com outside the US as well.


1. Not everyone works with ML ornis familiar with different types of neural nets

2. CNN exists outside of the US


A significant part are though and it would be helpful for that segment.


Can you give an example for your last sentence?


Here's a link: https://scipy-cookbook.readthedocs.io/items/ParallelProgramm... And a quote in italics below.

And, more importantly for us, while numpy is doing an array operation, python also releases the GIL. Thus if you tell one thread to do:

  print "%s %s %s %s and %s" %( ("spam",) *3 + ("eggs",) + ("spam",) )
  A = B + C
  print A
During the print operations and the % formatting operation, no other thread can execute. But during the A = B + C, another thread can run - and if you've written your code in a numpy style, much of the calculation will be done in a few array operations like A = B + C. Thus you can actually get a speedup from using multiple threads.


Can someone explain me why one would need a container orchestration system to train ml models? Why wouldn't one just stick with containers?


For the same reason you would use a container orchestration system for running anything: easier deployments, scaling, reliability, etc.


Atom + hydrogen addon Python 3 Keras and Tensorflow (I'm doing nlp)


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